56 lines
2.3 KiB
Python
56 lines
2.3 KiB
Python
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import os
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base1 = "/humgen/gsa-hphome1/chartl/projects/exome/coverage/whole_exome_broad/broad/"
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base2 = "/humgen/gsa-hphome1/chartl/projects/exome/coverage/whole_exome_broad/intersect/"
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def getField(fname,header):
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f = open(fname)
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h = f.readline().split("\t")
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idx = h.index(header)
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return map(lambda x: x.strip().split("\t")[idx],filter(lambda u: not u.startswith("Tot"),f.readlines()))
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def getFiles(base):
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num_jobs = len(os.listdir(base+"GATKDispatcher/"))
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sum_file = base+"GATKDispatcher/dispatch%d/job%d.sample_summary"
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int_file = base+"GATKDispatcher/dispatch%d/job%d.sample_interval_summary"
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files = map( lambda x: (sum_file % (x,x), int_file % (x,x)), range(num_jobs))
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return files
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def getBases(base):
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files = getFiles(base)
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lines = map(lambda x: getField(x[1],"Target"),files)
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sizes = map( lambda iList: reduce ( lambda u,v: u + v , map(lambda ival: int(ival.split(":")[1].split("-")[1])-int(ival.split(":")[1].split("-")[0]), iList ) ) , lines )
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return(sizes)
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def getPctAbove(base):
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files = getFiles(base)
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pct_above = map(lambda y: map(lambda z: float(z),y),map(lambda x: getField(x[0],"%_bases_above_20"),files))
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return pct_above
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def getTotals(base):
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files = getFiles(base)
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totals = map(lambda y: map(lambda z: int(z),y),map(lambda x: getField(x[0],"total"),files))
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return totals
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bases = getBases(base1) + getBases(base2)
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totals = getTotals(base1) + getTotals(base2)
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pct_above = getPctAbove(base1) + getPctAbove(base2)
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files = getFiles(base1) + getFiles(base2)
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total_bases = reduce(lambda u,v: u + v , bases)
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total_cvg = map(lambda u: 0, range(len(pct_above[0])))
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total_covered_20 = map(lambda u: 0, range(len(pct_above[0])))
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for f_idx in range(len(files)):
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for sam_idx in range(len(pct_above[0])):
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total_covered_20[sam_idx] += pct_above[f_idx][sam_idx]*bases[f_idx]
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total_cvg[sam_idx] += totals[f_idx][sam_idx]
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pct_above_20 = map( lambda x: x/total_bases, total_covered_20)
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mean_cvgs = map( lambda x: (x+0.0)/total_bases, total_cvg)
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#print(total_bases)
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#print(total_cvg)
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print("Mean\t%_above_20")
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mean_str = map(lambda u: "%.1f" % u, mean_cvgs)
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above_str = map(lambda u: "%.1f" % u, pct_above_20)
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print(reduce( lambda u,v: u + "\n" + v, map(lambda idx: mean_str[idx]+"\t"+above_str[idx],range(len(mean_str)))))
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